TU Bergakademie Freiberg Data Publications

Permanent URI for this collectionhttp://opara.zih.tu-dresden.de/handle/123456789/21

Data publications from research of Freiberg University of Mining and Technology.

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Browsing TU Bergakademie Freiberg Data Publications by Author "Ditscherlein, Ralf"

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  • ItemOpen Access
    2D Imaging Simulation from 3D Particle Data: Python Notebooks, Particle Datasets, and Simulation Results
    (Technische Universität Bergakademie Freiberg, 2024-05-14) Buchwald, Thomas; Ditscherlein, Ralf
    2D projection imaging techniques are simulated with 3D particle data from tomography measurements. This submission contains three distinct parts: original particle data, Python notebooks to simulate 2D imaging of the particles, and the resulting simulation dataset. The particle data comes as STLs that have been converted from VTK particle data as provided by the PARROT database (https://parrot.tu-freiberg.de/). The STL files are *not* identical with the STLs provided by PARROT as of May 2024! The particle data folder is provided as separate archive because of its large size. The Python notebooks were created with Jupyter Lab and Anaconda. A environment.yml file is provided that recreates the Anaconda environment. The simulation dataset that results from the provided Python notebooks is made available as CSV files or as pickled Python (pandas) DataFrames. Please refer to the included Readme for a detailed description of the files contained in the archive.
  • ItemOpen Access
    3 tomographic data sets of nano-CT measurements of a 30:70 vol-% mixture of talcum and saxolite
    (Technische Universität Bergakademie Freiberg, 2022-09-02) Ditscherlein, Ralf
    All 3 data sets are sub-volumes (Field of View approx. 65 µm) of a total sample of a particle mixture of talc and saxolite fixed in a matrix by means of epoxy resin and spacer particles (nanometre-sized carbon black particles, 150 nm equivalent spherical diameter). The primary analysis was carried out using nano-CT. The reconstructed result data are stored in the form of TIF files as sectional images (folder "rotated"). In addition, a correlation was carried out by means of EDXS analytics, the chemical information of which was used to train a segmentation algorithm. Since EDXS analysis requires a planar surface, the sample was further processed using FIB. The divergence of the ion beam produces a slight angular deviation from the perpendicular of the nano-CT volume, which necessitated a rotation of the initial volume data (--> "rotated"). The correlated result data of the particle-discrete phase information are also stored ("rotated segmented").
  • ItemOpen Access
    Epoxy-Based Particle Sample Preparation with Nano-Graphite as Spacer - RAW Data (Particle Sample Preparation) - Different mixtures (by volume) of graphite-nanoparticles and analysis particles
    (Technische Universität Bergakademie Freiberg, 2020-05-08) Ditscherlein, Ralf
    To get good image segmentation results in tomographic analysis methods, particles has to be seperated from each other while embedding them into a matrix. Low X-ray absorbing nano-graphite below the voxel resolution of the system is mixed with the analysis particles to form a shell to avoid direct particle-particle contact. After mixing it with epoxy resin, the paste is sucked into a polymeric tube of 2 mm inner diameter. After hardening, the formed cylinder was scanned with an X-ray microscope (ZEISS Xradia Versa 510) with the following parameters: 80 keV, 7 W, 360°, 2001 projections, 1 s exposure time, 2 µm voxel size, binning 2. After scannning, the following filters were applied while reconstruction with ZEISS reconstructor: Beam Hardening Correction 0.05, Smoothing 0,7. Detailed overview of the parameters is summarized as screenshots within the repository. To determine an optimal mixture of the two components, the following volume-fractions were analysed: Nanoparticle:Particle 20vol-%:80vol-% 40vol-%:60vol-% 60vol-%:40vol-%
  • ItemOpen Access
    Multi-Scale Tomographic Analysis for Micron-Sized Particulate Samples - RAW Data
    (Technische Universität Bergakademie Freiberg, 2020-01-08) Ditscherlein, Ralf; Martins de Souza e Silva, Juliana
    This repository includes the reconstructed TIFF-files from multiple scale tomographic analysis of particles in an embedding matrix (overall volume and 3 sub-volumes in 2 different magnification steps): LARGE (low-resolution) (due to filesize partioned in part I, II, III, IV and V) 1 large volume of particle mixture (50/50) of spheres (0.2 - 2 µm) and fibres (diameter: 10 µm length: 100 - 1000 µm) embedded in a matrix (wax, 15 vol-%). The large volume was extracted with an automated syringe into a small polymeric tube (diameter: 1.8 mm) and shock frozen. After that the sample was mounted on top of a needle pin and scanned with a micro-CT (ZEISS Versa510) at 80 keV, 7 W, low energy filter LE4, exposure time 2 s, optical magn. 4x, 3201 projections, 360°, Binning 2, Voxelsize 1.5 µm SubSample - MEDIUM (medium-resolution) (SubSample 1, 2, 3) After the scan, the LARGE volume was cutted in small disks and cutted a second time in little bars. Again, mounted on top of a needle pin and scanned with same parameters, BUT with 40x optical magnification and 25 s exposure time to go down to a system limit of 0.3 µm Voxelsize (again with ZEISS VERSA510). This was done 3 times in different heights of the LARGE volume SubSample - HIGH (high-resolution) (SubSample 1, 2, 3) After that, all SubSamples were scanned again with a nano-CT (ZEISS ULTRA810) at 5.4 keV, 60 s exposure time, 901 projections, 180°, Binning 1 to reach Voxelsize of 0.064 µm
  • ItemOpen Access
    Supplemental SEM-EDS (MLA) and CT data for the publication "CNN-based 3D characterization and liberation analysis of lithium-bearing slag particles using correlative CT and SEM imaging"
    (Technische Universität Bergakademie Freiberg, 2026-05-13) Ditscherlein, Ralf
    This dataset provides the underlying X-ray CT data and processed image stacks used for particle-scale characterization and evaluation of the proposed workflow. The study addresses the challenge of accurately characterizing lithium-bearing slag particles to improve recovery of critical raw materials. A correlative workflow combining 3D CT imaging with 2D SEM-based mineral maps is used to train convolutional neural networks for phase-wise and particle-wise segmentation. This enables scalable 3D characterization with minimal manual labeling effort. The models are applied to particle size fractions of 63–100 µm and 100–250 µm. Results show that conventional 2D approaches systematically overestimate mineral liberation, while the presented 3D approach reduces stereological bias and provides more reliable input for process optimization.
  • ItemOpen Access
    Tomographic dataset of a particulate Al2O3 sample
    (Technische Universität Bergakademie Freiberg, 2021-02-26) Ditscherlein, Ralf
    Al2O3 particle samples embedded in wax and scanned with tomograph Zeiss Xradia Versa 510 Particle sample is segmented via a standard workflow in Fiji (ImageJ) and provided as "segmented.zip" Resulting discrete particles are stored within the PARROT database (https://parrot.tu-freiberg.de)
  • ItemOpen Access
    Tomographic dataset of a particulate Dolomite sample
    (Technische Universität Bergakademie Freiberg, 2021-02-26) Ditscherlein, Ralf
    Dolomite particle samples embedded in wax and scanned with tomograph Zeiss Xradia Versa 510 Particle sample is segmented via a standard workflow in Fiji (ImageJ) and provided as "segmented.zip" Resulting discrete particles are stored within the PARROT database (https://parrot.tu-freiberg.de)
  • ItemOpen Access
    Tomographic dataset of a particulate Limstone sample
    (Technische Universität Bergakademie Freiberg, 2021-02-26) Ditscherlein, Ralf
    Limestone particle samples embedded in wax and scanned with tomograph Zeiss Xradia Versa 510. Particle sample is segmented via a standard workflow in Fiji (ImageJ) and provided as "segmented.zip" Resulting discrete particles are stored within the PARROT database (https://parrot.tu-freiberg.de)
  • ItemOpen Access
    Tomographic dataset of a particulate Mica sample
    (Technische Universität Bergakademie Freiberg, 2021-02-26) Ditscherlein, Ralf
    Mica particle samples embedded in wax and scanned with tomograph Zeiss Xradia Versa 510 Particle sample is segmented via a standard workflow in Fiji (ImageJ) and provided as "segmented.zip" Resulting discrete particles are stored within the PARROT database (https://parrot.tu-freiberg.de)
  • ItemOpen Access
    Tomographic dataset of a particulate Quartz sample
    (Technische Universität Bergakademie Freiberg, 2021-02-26) Ditscherlein, Ralf
    Quartz particle samples embedded in wax and scanned with tomograph Zeiss Xradia Versa 510 Particle sample is segmented via a standard workflow in Fiji (ImageJ) and provided as "segmented.zip" Resulting discrete particles are stored within the PARROT database (https://parrot.tu-freiberg.de)
  • ItemOpen Access
    Tomographic dataset of a particulate Soda-lime glass sample
    (Technische Universität Bergakademie Freiberg, 2021-02-26) Ditscherlein, Ralf
    Soda-lime glass particle samples embedded in epoxy resin mixed with graphite nanoparticles as spacer and scanned with tomograph Zeiss Xradia Versa 510 Particle sample is segmented via a standard workflow in Fiji (ImageJ) and provided as "segmented.zip" Resulting discrete particles are stored within the PARROT database (https://parrot.tu-freiberg.de)
  • ItemOpen Access
    X-ray CT Data of Lunar Regolith Simulants and Gray Value Sensitive Simulation Data
    (Technische Universität Bergakademie Freiberg, 2026-02-18) Ditscherlein, Ralf
    This dataset provides reconstructed X-ray microtomography data of four lunar regolith simulants together with simulated data for method evaluation. The dataset enables reproducibility of the particle fingerprint visualization technique, supports exploration of imaging artifacts, and provides reference implementations in Python. It is intended for use in particle system characterization, image analysis, and method benchmarking.